1- What types of business situations or problems might best lend themselves to multiple linear regression? What types may not? Explain
2- Give an example based on your experience of a situation in which using a multiple regression model or non-linear regression model may have helped you make a better decision.
Complete Problems 4-22 and 4-23.
Complete Problem 4-24. In addition to the questions in this problem, respond to the following:
- State the linear equation.
- Explain the overall statistical significance of the model.
- Explain the statistical significance for each independent variable in the model
- Interpret the Adjusted R2.
- Is this a good predictive equation(s)? Which variables should be excluded (if any) and why? Explain.
Complete Problem 4-30.
Use Excel’s regression option to perform the regression. Use one Excel spreadsheet file for the calculations and explanations, with one worksheet per problem. Use the problem number for each worksheet name. Cells should contain the formulas (i.e., if a formula was used to calculate the entry in that cell).
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